Desenvolvimento de uma ferramenta automatizada para avaliação do desempenho de fundos de investimentos no Brasil

Abstract

This work aims to develop an automated tool to assist in the selection of investment funds. The goal is to demonstrate that it is possible to identify high-performing funds by applying the Sharpe, Treynor, and Modigliani indices, widely used by fund managers and well-established in the financial market. These indices help identify funds that are safe, efficient, and deliver superior performance. The development was carried out using Google Colab, an online platform that enables the execution of Python code without installation and at no cost. The fund data was downloaded automatically from the open data portal of the Comissão de Valores Mobiliários (CVM). With the implementation of the code and the results of conducted tests, it was possible to identify top-performing funds, achieving results above the Certificado de Depósito Bancário (CDI), which is the benchmark commonly used for performance comparison.